Identification of Microturbine Model for Long-term Dynamic Analysis of Distribution Networks

As one of the most successfully commercialized distributed energy resources, the long-term effects of microturbines (MTs) on the distribution network has not been fully investigated due to the complex thermo-fluid-mechanical energy conversion processes. This is further complicated by the fact that the parameter and internal data of MTs are not always available to the electric utility, due to different ownerships and confidentiality concerns. To address this issue, a general modeling approach for MTs is proposed in this paper, which allows for the long-term simulation of the distribution network with multiple MTs. First, the feasibility of deriving a simplified MT model for long-term dynamic analysis of the distribution network is discussed, based on the physical understanding of dynamic processes that occurred within MTs. Then a three-stage identification method is developed in order to obtain a piecewise MT model and predict electro-mechanical system behaviors with saturation. Next, assisted with the electric power flow calculation tool, a fast simulation methodology is proposed to evaluate the long-term impact of multiple MTs on the distribution network. Finally, the model is verified by using Capstone C30 microturbine experiments, and further applied to the dynamic simulation of a modified IEEE 37-node test feeder with promising results.

Patient-reported quality-of-life analysis of radium-223 dichloride from the phase III ALSYMPCA study

BACKGROUND: Radium-223 dichloride (radium-223), a first-in-class α-emitting radiopharmaceutical, is recommended in both pre- and post-docetaxel settings in patients with castration-resistant prostate cancer (CRPC) and symptomatic bone metastases based on overall survival benefit demonstrated in the phase III ALSYMPCA study. ALSYMPCA included prospective measurements of health-related quality of life (QOL) using two validated instruments: the general EuroQoL 5D (EQ-5D) and the disease-specific Functional Assessment of Cancer Therapy-Prostate (FACT-P).

PATIENTS AND METHODS: Analyses were conducted to determine treatment effects of radium-223 plus standard of care (SOC) versus placebo plus SOC on QOL using FACT-P and EQ-5D. Outcomes assessed were percentage of patients experiencing improvement, percentage of patients experiencing worsening, and mean QOL scores during the study.

RESULTS: Analyses were carried out on the intent-to-treat population of patients randomized to receive radium-223 (n = 614) or placebo (n = 307). The mean baseline EQ-5D utility and FACT-P total scores were similar between treatment groups. A significantly higher percentage of patients receiving radium-223 experienced meaningful improvement in EQ-5D utility score on treatment versus placebo {29.2% versus 18.5%, respectively; P = 0.004; odds ratio (OR) = 1.82 [95% confidence interval (CI) 1.21-2.74]}. Findings were similar for FACT-P total score [24.6% versus 16.1%, respectively; P = 0.020; OR = 1.70 (95% CI 1.08-2.65)]. A lower percentage of patients receiving radium-223 experienced meaningful worsening versus placebo measured by EQ-5D utility score and FACT-P total score. Prior docetaxel use and current bisphosphonate use did not affect these findings. Treatment was a significant predictor of EQ-5D utility score, with radium-223 associated with higher scores versus placebo (0.56 versus 0.50, respectively; P = 0.002). Findings were similar for FACT-P total score (99.08 versus 95.22, respectively; P = 0.004).

CONCLUSIONS: QOL data from ALSYMPCA demonstrated that improved survival with radium-223 is accompanied by significant QOL benefits, including a higher percentage of patients with meaningful QOL improvement and a slower decline in QOL over time in patients with CRPC.

Diagnostic utility of thyroglobulin measurement in the fine needle aspirates from cervical lymph nodes: a case report

Fine needle aspiration cytology (FNAC) is the more accurate diagnostic method for cervical lymph node (CLN) metastasis from differentiated thyroid cancers (DTC). However, FNAC diagnosis of cystic CLN is, in most cases, uninformative due to inadequate cellularity. Recently, thyroglobulin (Tg) detection in FNAC needle washout fluid has been shown to improve the diagnostic accuracy of FNAC, and its routine association with cytology is recommended. We here describe the case of a 20 yr old girl complaining of the recent appearance of palpable non-painful laterocervical nodes in the neck. Ultrasound examination revealed the presence of 3 cystic CLNs and 2 mixed thyroid nodules, with the larger one showing irregular margins. On the latter, and on 2 larger CLNs, FNAC was performed, and both Tg protein and mRNA were determined in the needle washout. The cytological analysis was not diagnostic for the two CLNs, while that of the thyroid nodule reported the presence of colloid and groups of thyrocytes with normal morphology. Both CLNs showed, however, high levels of Tg protein and were positive for Tg mRNA, suggestive of metastatic DTC. Based on these findings, the FNAC analysis was performed on the second smaller thyroid nodule suggesting (Tir4) the presence of PTC. The patient was then subjected to total thyroidectomy with lymph nodes resection of the central and homolateral compartments. The histological diagnosis confirmed the presence of a PTC in the small nodule and metastatic lymph nodes. In conclusion, this case confirms that the cytological diagnosis of cystic lymph nodes is challenging, and that the measurement of Tg protein and/or mRNA in the needle washout may overcome this limitation.

Analysis on the connotation of probability in the artificial intelligence algorithm for economic decision making.

This paper analyzes the inner relations between classical sub-scheme probability and statistic probability, subjective probability and objective probability, prior probability and posterior probability, transition probability and probability of utility, and further analysis the goal, method, and its practical economic purpose which represent by these various probability from the perspective of mathematics, so as to deeply understand there connotation and its relation with economic decision making, thus will pave the route for scientific predication and decision making.

An investigation of the clinical utility of preoperative cardiopulmonary exercise testing in patients undergoing major pancreatic surgery

Pancreaticoduodenectomy with or without adjuvant chemotherapy remains the only modality of possible cure in patients with cancer involving the head of the pancreas and the periampullary region. While mortality rates after pancreaticoduodenectomy have improved considerably over the course of the last century, morbidity remains high. Patient selection is of paramount importance in ensuring that major surgery is offered to individuals who will most benefit from a pancreaticoduodenectomy. Moreover, identifying preoperative risk factors provides potential targets for prehabilitation and optimisation of the patient's physiology before undertaking surgery. In addition to this, early identification of patients who are likely to develop postoperative complications allows for better allocation of critical care resources and more aggressive management high risk patients. Cardiopulmonary exercise testing is becoming an increasingly popular tool in the preoperative risk assessment of the surgical patient. However, very little work has been done to investigate the role of cardiopulmonary exercise testing in predicting complications after pancreaticoduodenectomy. The impact of jaundice, systemic inflammation and other preoperative clinicopathological characteristics on cardiopulmonary exercise physiology has not been studied in detail before in this cohort of patients. The overall aim of the thesis was to examine the relationships between preoperative clinico-pathological characteristics including cardiopulmonary exercise physiology, obstructive jaundice, body composition and systemic inflammation and complications and the post-surgical systemic inflammatory response in patients undergoing pancreaticoduodenectomy. Chapter 1 reviews the existing literature on preoperative cardiopulmonary exercise testing, the impact of obstructive jaundice, perioperative systemic inflammation and the importance of body composition in determining outcomes in patients undergoing major surgery with particular reference to pancreatic surgery. Chapter 2 reports on the role of cardiopulmonary exercise testing in predicting postoperative complications after pancreaticoduodenectomy. The results demonstrate that patients with V˙O2AT less than 10 ml/kg/min are more likely to develop a postoperative pancreatic fistula, stay longer in hospital and less likely to receive adjuvant therapy. These results emphasise the importance of aerobic fitness to recover from the operative stress of major surgery without significant morbidity. Cardiopulmonary exercise testing may prove useful in selecting patients for intensive prehabilitation programmes as well as for other optimisation measures to prepare them for major surgery. Chapter 3 evaluates the relationship between cardiopulmonary exercise physiology and other clinicopathological characteristics of the patient. A detailed analysis of cardiopulmonary exercise test parameters in jaundiced versus non-jaundiced patients demonstrates that obstructive jaundice does not impair cardiopulmonary exercise physiology. This further supports emerging evidence in contemporary literature that jaundiced patients can proceed directly to surgery without preoperative biliary drainage. The results of this study also show an interesting inverse relationship between body mass index and anaerobic threshold which is analysed in more detail in Chapter 4. Chapter 4 examines the relationship between preoperative cardiopulmonary exercise physiology and body composition in depth. All parameters measured at cardiopulmonary exercise test are compared against body composition and body mass index. The results of this chapter report that the current method of reporting V˙O2, both at peak exercise and anaerobic threshold, is biased against obese subjects and advises caution in the interpretation of cardiopulmonary exercise test results in patients with a high BMI. This is particularly important as current evidence in literature suggests that postoperative outcomes in obese subjects are comparable to non-obese subjects while cardiopulmonary exercise test results are also abnormally low in this very same cohort of patients. Chapter 5 analyses the relationship between preoperative clinico-pathological characteristics including systemic inflammation and the magnitude of the postoperative systemic inflammatory response. Obstructive jaundice appears to have an immunosuppressive effect while elevated preoperative CRP and hypoalbuminemia appear to have opposite effects with hypoalbuminemia resulting in a lower response while elevated CRP in the absence of hypoalbuminemia resulted in a greater postoperative systemic inflammatory response. Chapter 6 evaluates the role of the early postoperative systemic inflammatory response in predicting complications after pancreaticoduodenectomy and aims to establish clinically relevant thresholds for C-Reactive Protein for the prediction of complications. The results of this chapter demonstrate that CRP levels as early as the second postoperative day are associated with complications. While post-operative CRP was useful in the prediction of infective complications, this was the case only in patients who did not develop a post-operative pancreatic fistula. The predictive ability of inflammatory markers for infectious complications was blunted in patients with a pancreatic fistula. Chapter 7 summarises the findings of this thesis, their place in current literature and future directions. The results of this thesis add to the current knowledge regarding the complex pathophysiological abnormalities in patients undergoing pancreaticoduodenectomy, with specific emphasis on the interaction between cardiopulmonary exercise physiology, obstructive jaundice, systemic inflammation and postoperative outcomes. The work presented in this thesis lays the foundations for further studies aimed at improving outcomes after pancreaticoduodenectomy through the development of individualised, goal-directed therapies that are initiated well before this morbid yet necessary operation is performed.

Computational Analysis of Intelligent Agents: Social and Strategic Settings

The central motif of this work is prediction and optimization in presence of multiple interacting intelligent agents. We use the phrase `intelligent agents' to imply in some sense, a `bounded rationality', the exact meaning of which varies depending on the setting. Our agents may not be `rational' in the classical game theoretic sense, in that they don't always optimize a global objective. Rather, they rely on heuristics, as is natural for human agents or even software agents operating in the real-world. Within this broad framework we study the problem of influence maximization in social networks where behavior of agents is myopic, but complication stems from the structure of interaction networks. In this setting, we generalize two well-known models and give new algorithms and hardness results for our models. Then we move on to models where the agents reason strategically but are faced with considerable uncertainty. For such games, we give a new solution concept and analyze a real-world game using out techniques. Finally, the richest model we consider is that of Network Cournot Competition which deals with strategic resource allocation in hypergraphs, where agents reason strategically and their interaction is specified indirectly via player's utility functions. For this model, we give the first equilibrium computability results. In all of the above problems, we assume that payoffs for the agents are known. However, for real-world games, getting the payoffs can be quite challenging. To this end, we also study the inverse problem of inferring payoffs, given game history. We propose and evaluate a data analytic framework and we show that it is fast and performant.

Sorghum Crop Modeling and Its Utility in Agronomy and Breeding

Crop models are simplified mathematical representations of the interacting biological and environmental components of the dynamic soil–plant–environment system. Sorghum crop modeling has evolved in parallel with crop modeling capability in general, since its origins in the 1960s and 1970s. Here we briefly review the trajectory in sorghum crop modeling leading to the development of advanced models. We then (i) overview the structure and function of the sorghum model in the Agricultural Production System sIMulator (APSIM) to exemplify advanced modeling concepts that suit both agronomic and breeding applications, (ii) review an example of use of sorghum modeling in supporting agronomic management decisions, (iii) review an example of the use of sorghum modeling in plant breeding, and (iv) consider implications for future roles of sorghum crop modeling. Modeling and simulation provide an avenue to explore consequences of crop management decision options in situations confronted with risks associated with seasonal climate uncertainties. Here we consider the possibility of manipulating planting configuration and density in sorghum as a means to manipulate the productivity–risk trade-off. A simulation analysis of decision options is presented and avenues for its use with decision-makers discussed. Modeling and simulation also provide opportunities to improve breeding efficiency by either dissecting complex traits to more amenable targets for genetics and breeding, or by trait evaluation via phenotypic prediction in target production regions to help prioritize effort and assess breeding strategies. Here we consider studies on the stay-green trait in sorghum, which confers yield advantage in water-limited situations, to exemplify both aspects. The possible future roles of sorghum modeling in agronomy and breeding are discussed as are opportunities related to their synergistic interaction. The potential to add significant value to the revolution in plant breeding associated with genomic technologies is identified as the new modeling frontier.

Diagnóstico ecográfico de tumores anexiais: modelos do grupo international ovary tumor analysis (IOTA) versus classificação gynecologic imaging report and data system (GI-RADS)

A ecografia é o exame de primeira linha na identificação e caraterização de tumores anexiais. Foram descritos diversos métodos de diagnóstico diferencial incluindo a avaliação subjetiva do observador, índices descritivos simples e índices matematicamente desenvolvidos como modelos de regressão logística, continuando a avaliação subjectiva por examinador diferenciado a ser o melhor método de discriminação entre tumores malignos e benignos. No entanto, devido à subjectividade inerente a esta avaliação tornouse necessário estabelecer uma nomenclatura padronizada e uma classificação que facilitasse a comunicação de resultados e respectivas recomendações de vigilância. O objetivo deste artigo é resumir e comparar diferentes métodos de avaliação e classificação de tumores anexiais, nomeadamente os modelos do grupo International Ovary Tumor Analysis (IOTA) e a classificação Gynecologic Imaging Report and Data System (GI-RADS), em termos de desempenho diagnóstico e utilidade na prática clínica.

Bioorthogonal Noncanonical Amino Acid Tagging for Selective Analysis of the Pseudomonas aeruginosa Proteome

In natural environments, bacterial physiology is frequently characterized by slow metabolic rates and complex cellular heterogeneities. The opportunistic pathogen Pseudomonas aeruginosa provides one such example; P. aeruginosa forms untreatable chronic biofilm infections of the cystic fibrosis lung, where oxygen limitation can lead to states of metabolic dormancy. To better understand the biology of these states, in vitro experiments must be adapted to better recapitulate natural settings. However, low rates of protein turnover and cellular or phenotypic complexity make these systems difficult to study using established methods. Here we adapt the bioorthogonal noncanonical amino acid tagging (BONCAT) method for time- and cell-selective proteomic analysis to the study of P. aeruginosa. Analysis of proteins synthesized in an anoxic dormancy state led to the discovery of a new type of transcriptional regulator which we designated SutA. We performed detailed analyses of SutA’s role in transcription under slow growth states and we elucidated the structural basis for its regulatory behavior. Additionally, we used cell-selective targeting of BONCAT labeling to measure the dynamic proteomic response of an antibiotic-tolerant biofilm subpopulation. Overall this work shows the utility of selective proteomics as applied to bacterial physiology and describes the broad biological insight obtained from that application.

Age-Dependent Fragility and Life-Cycle Cost Analysis of Timber and Steel Distribution Poles Subjected to Hurricanes

Power distribution systems are susceptible to extreme damage from natural hazards especially hurricanes. Hurricane winds can knock down distribution poles thereby causing damage to the system and power outages which can result in millions of dollars in lost revenue and restoration costs. Timber has been the dominant material used to support overhead lines in distribution systems. Recently however, utility companies have been searching for a cost-effective alternative to timber poles due to environmental concerns, durability, high cost of maintenance and need for improved aesthetics. Steel has emerged as a viable alternative to timber due to its advantages such as relatively lower maintenance cost, light weight, consistent performance, and invulnerability to wood-pecker attacks. Both timber and steel poles are prone to deterioration over time due to decay in the timber and corrosion of the steel. This research proposes a framework for conducting fragility analysis of timber and steel poles subjected to hurricane winds considering deterioration of the poles over time. Monte Carlo simulation was used to develop the fragility curves considering uncertainties in strength, geometry and wind loads. A framework for life-cycle cost analysis is also proposed to compare the steel and timber poles. The results show that steel poles can have superior reliability and lower life-cycle cost compared to timber poles, which makes them suitable substitutes.

Geographic Provenancing of Unprocessed Cotton Using Elemental Analysis and Stable Isotope Ratios

Cotton is the most abundant natural fiber in the world. Many countries are involved in the growing, importation, exportation and production of this commodity. Paper documentation claiming geographic origin is the current method employed at U.S. ports for identifying cotton sources and enforcing tariffs. Because customs documentation can be easily falsified, it is necessary to develop a robust method for authenticating or refuting the source of the cotton commodities. This work presents, for the first time, a comprehensive approach to the chemical characterization of unprocessed cotton in order to provide an independent tool to establish geographic origin. Elemental and stable isotope ratio analysis of unprocessed cotton provides a means to increase the ability to distinguish cotton in addition to any physical and morphological examinations that could be, and are currently performed. Elemental analysis has been conducted using LA-ICP-MS, LA-ICP-OES and LIBS in order to offer a direct comparison of the analytical performance of each technique and determine the utility of each technique for this purpose. Multivariate predictive modeling approaches are used to determine the potential of elemental and stable isotopic information to aide in the geographic provenancing of unprocessed cotton of both domestic and foreign origin. These approaches assess the stability of the profiles to temporal and spatial variation to determine the feasibility of this application. This dissertation also evaluates plasma conditions and ablation processes so as to improve the quality of analytical measurements made using atomic emission spectroscopy techniques. These interactions, in LIBS particularly, are assessed to determine any potential simplification of the instrumental design and method development phases. This is accomplished through the analysis of several matrices representing different physical substrates to determine the potential of adopting universal LIBS parameters for 532 nm and 1064 nm LIBS for some important operating parameters. A novel approach to evaluate both ablation processes and plasma conditions using a single measurement was developed and utilized to determine the “useful ablation efficiency” for different materials. The work presented here demonstrates the potential for an a priori prediction of some probable laser parameters important in analytical LIBS measurement.

¬FISH DISTRIBUTIONS IN LAKE ONTARIO’S EASTERN BASIN AND THE UPPER ST. LAWRENCE RIVER: AN ANALYSIS USING GIS AND OCCUPANCY MODELLING TECHNIQUES

Predictive models of species distributions are important tools for fisheries management. Unfortunately, these predictive models can be difficult to perform on large waterbodies where fish are difficult to detect and exhaustive sampling is not possible. In recent years the development of Geographic Information Systems (GIS) and new occupancy modelling techniques has improved our ability to predict distributions across landscapes as well as account for imperfect detection. I surveyed the nearshore fish community at 105 sites between Kingston, Ontario and Rockport, Ontario with the objective of modelling geographic and environmental characteristics associated with littoral fish distributions. Occupancy modelling was performed on Round Goby, Yellow perch, and Lepomis spp. Modelling with geographic and environmental covariates revealed the effect of shoreline exposure on nearshore habitat characteristics and the occupancy of Round Goby. Yellow Perch, and Lepomis spp. occupancy was most strongly associated negatively with distance to a wetland. These results are consistent with past research on large lake systems indicate the importance of wetlands and shoreline exposure in determining the fish community of the littoral zone. By examining 3 species with varying rates of occupancy and detection, this study was also able to demonstrate the variable utility of occupancy modelling.

Climate Change Adaptation Case Study: Benefit-Cost Analysis of Coastal Flooding Hazard Mitigation

The damage Hurricane Sandy caused had far-reaching repercussions up and down the East Coast of the United States. Vast coastal flooding accompanied the storm, inundating homes, businesses, and utility and emergency facilities. Since the storm, projects to mitigate similar future floods have been scrutinized. Such projects not only need to keep out floodwaters but also be designed to withstand the effect that climate change might have on rising sea levels and increased flood risk. In this study, we develop an economic model to assess the costs and benefits of a berm (sea wall) to mitigate the effects of flooding from a large storm. We account for the lifecycle costs of the project, which include those for the upfront construction of the berm, ongoing maintenance, land acquisition, and wetland and recreation zone construction. Benefits of the project include avoided fatalities, avoided residential and commercial damages, avoided utility and municipal damages, recreational and health benefits, avoided debris removal expenses, and avoided loss of function of key transportation and commercial infrastructure located in the area. Our estimate of the beneficial effects of the berm includes ecosystem services from wetlands and health benefits to the surrounding community from a park and nature system constructed along the berm. To account for the effects of climate change and verify that the project will maintain its effectiveness over the long term, we allow the risk of flooding to increase over time. Over our 50-year time horizon, we double the risk of 100- and 500-year flood events to account for the effects of sea level rise on coastal flooding. Based on the economic analysis, the project is highly cost beneficial over its 50-year timeframe. This analysis demonstrates that climate change adaptation investments can be cost beneficial even though they mitigate the impacts of low-probability, high-consequence events.

An investigation into the utility of the Mini Addenbrooke's Cognitive Examination (M-ACE) for the early detection of dementia and mild cognitive impairment in people aged 75 and over

Background/Aims: The Mini Addenbrooke’s Cognitive Examination (M-ACE) is the abbreviated version of the widely-used Addenbrooke’s Cognitive Examination (ACE-III), a cognitive screening tool that is used internationally in the assessment of mild cognitive impairment (MCI) and dementia. The objectives of this study were to investigate the diagnostic accuracy of the M-ACE with individuals aged 75 and over to distinguish between those who do and do not have a dementia or MCI, and also to establish whether the cut-off scores recommended by Hsieh et al. (2014) [9] in the original validation study for the M-ACE are optimal for this age group. Methods: The M-ACE was administered to 58 participants (24 with a diagnosis of dementia, 17 with a diagnosis of MCI and 17 healthy controls). The extent to which scores distinguished between groups (dementia, MCI or no diagnosis) was explored using receiver operating characteristic curve analysis. Results: The optimal cut-off for detecting dementia was ≤ 21/30 (score ≤ 21/30 indicating dementia with a sensitivity of 0.95, a specificity of 1 and a positive predictive value of 1) compared to the original higher published cut-off of ≤ 25/30 (sensitivity of 0.95, specificity of 0.70 and a positive predictive value of 0.82 in this sample). Conclusions: The M-ACE has excellent diagnostic accuracy for the detection of dementia in a UK clinical sample. It may be necessary to consider lower cut-offs than those given in the original validation study.